{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T06:58:52Z","timestamp":1790492332864,"version":"4.1.0"},"reference-count":41,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T00:00:00Z","timestamp":1669075200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology of Taiwan","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Deep learning models (DLMs) have shown superiority in electrocardiogram (ECG) analysis and have been applied to diagnose dyskalaemias. However, no study has explored the performance of DLM-enabled ECG in continuous follow-up scenarios. Therefore, we proposed a dynamic revision of DLM-enabled ECG to use personal pre-annotated ECGs to enhance the accuracy in patients with multiple visits.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>We retrospectively collected 168 450 ECGs with corresponding serum potassium (K+) levels from 103 091 patients as development samples. In the internal\/external validation sets, the numbers of ECGs with corresponding K+ were 37 246\/47 604 from 13 555\/20 058 patients. Our dynamic revision method showed better performance than the traditional direct prediction for diagnosing hypokalaemia [area under the receiver operating characteristic curve (AUC) = 0.730\/0.720\u20130.788\/0.778] and hyperkalaemia (AUC = 0.884\/0.888\u20130.915\/0.908) in patients with multiple visits.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our method has shown a distinguishable improvement in DLMs for diagnosing dyskalaemias in patients with multiple visits, and we also proved its application in ejection fraction prediction, which could further improve daily clinical practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ehjdh\/ztac072","type":"journal-article","created":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T13:09:58Z","timestamp":1669122598000},"page":"22-32","source":"Crossref","is-referenced-by-count":12,"title":["Development and validation of a dynamic deep learning algorithm using electrocardiogram to predict dyskalaemias in patients with multiple visits"],"prefix":"10.1093","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9115-2656","authenticated-orcid":false,"given":"Yu-Sheng","family":"Lou","sequence":"first","affiliation":[{"name":"Graduate Institutes of Life Sciences, National Defense Medical Center , No.161, Min-Chun E. 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Rd., Section 6, Neihu, Taipei 114, Taiwan , Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5167-8327","authenticated-orcid":false,"given":"Chin-Sheng","family":"Lin","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, , No. 325, Cheng-Kung Rd., Section 2, Neihu, Taipei 114, Taiwan , Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0574-5736","authenticated-orcid":false,"given":"Wen-Hui","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Family and Community Medicine, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center , No. 325, Cheng-Kung Rd., Section 2, Neihu, Taipei 114, Taiwan , Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7450-504X","authenticated-orcid":false,"given":"Chia-Cheng","family":"Lee","sequence":"additional","affiliation":[{"name":"Medical Informatics Office, Tri-Service General Hospital, National Defense Medical Center , No. 325, Cheng- Kung Rd., Section 2, Neihu, Taipei 114, Taiwan , Republic of China"},{"name":"Division of Colorectal Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center , No. 325, Cheng-Kung Rd., Section 2, Neihu, Taipei 114, Taiwan , Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chih-Hung","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology-Head and Neck Surgery, Tri-Service General Hospital, National Defense Medical Center , No. 325, Cheng-Kung Rd., Section 2, Neihu, Taipei 114, Taiwan , Republic of China"},{"name":"Graduate Institute of Medical Sciences, National Defense Medical Center , No. 161, Min-Chun E. 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